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Senior Data Engineer

Senior Data Engineer

OttoBauthenticJohannesburg, South Africa
30+ days ago
Job description

Job Summary :

  • To lead the design, development, and governance of the company’s enterprise data infrastructure, transitioning from the current SSIS-based ETL environment to a modern, scalable, Azure-based cloud data warehouse.
  • This role is strategic and collaborative, requiring close engagement with business leaders, BI developers, analysts, and IT teams to ensure data solutions are business-aligned, governance-compliant, and ready for advanced analytics.
  • As a senior member of the team, the role will mentor junior data engineers, influence architectural decisions, and champion best practices across the organisation.

Key Responsibilities :

Data Warehouse Architecture & Leadership

  • Lead the architectural design and implementation of the new Azure-based data warehouse.
  • Oversee the optimisation of the existing SSIS-based ETL environment during the transition phase.

    Establish long-term data platform strategy in collaboration with BI and IT leadership.

    Data Governance & Compliance

  • Own the data governance framework, ensuring standards for data quality, security, lineage, and access control are embedded in all solutions
  • Partner with compliance and legal teams to meet regulatory requirements for data storage and processing.
  • Champion the use of data cataloguing and metadata management tools.
  • Collaboration & Stakeholder Engagement

  • Work directly with senior stakeholders across business units to translate needs into actionable technical solutions.
  • Serve as the primary point of contact between the BI team, engineering, and external vendors for data infrastructure matters.
  • Facilitate workshops, architectural reviews, and cross-team solution design sessions.
  • Technical Delivery & Mentorship

  • Lead the build, testing, and deployment of robust ETL / ELT pipelines for multi-source integration.
  • Ensure smooth migration of historical and real-time data to the new warehouse with minimal downtime.
  • Mentor and support junior and mid-level engineers in technical best practices and solution delivery.
  • Performance Monitoring & Continuous Improvement

  • Implement platform monitoring solutions to track and optimise performance.
  • Drive continuous improvement in architecture, tooling, and governance processes
  • Required Skills and Qualifications :

    EDUCATION

    Mandatory :

  • Bachelor’s degree in Computer Science, Information Systems, Data Engineering, or related field.
  • Preferred :

  • Master’s degree in Data Engineering, Computer Science, or related discipline.
  • Business Management or Project Management certification to support stakeholder engagement and project oversight.
  • Azure Data Engineer Associate or equivalent cloud certification.
  • Data governance certification (DAMA, DCAM, or equivalent).
  • EXPERIENCE & SKILLS / PHYSICAL COMPETENCIES

    Technical Experience

    Mandatory :

  • 5+ years in data engineering, with experience in data warehouse design and development.
  • Strong hands-on experience with SSIS for ETL processes.
  • Proven expertise in Azure Data Platform components (Azure Data Factory, Azure Synapse Analytics, Azure SQL Database, Data Lake Storage).
  • Strong SQL skills (T-SQL preferred).
  • Experience implementing data governance principles, including data quality frameworks, security / access controls, and metadata management.
  • Experience with data modeling (Kimball / Star Schema / Snowflake).
  • Proficient in performance tuning and troubleshooting data processes.
  • Preferred :

  • Experience with Python or other scripting languages for data processing and automation.
  • Knowledge of Azure Purview or other data catalog solutions.
  • Knowledge of Azure DevOps, CI / CD pipelines for data solutions.
  • Power BI integration experience with Azure datasets.
  • Physical & Technical Competencies

  • Ability to design and optimize complex ETL / ELT workflows.
  • Strong understanding of data governance frameworks and compliance requirements.
  • Proficient in working with large-scale data sets and high-volume data pipelines.
  • Strong problem-solving skills with a focus on automation and efficiency.
  • Proficient in version control tools (e.g., Git).
  • Expertise in optimising data platforms for scale and performance.
  • Ability to manage competing priorities across multiple projects
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